Search: “model-releases”

Deflickering Vision-Based Occupancy Networks through Lightweight Spatio-Temporal Correlation

arXiv:2502.15438v5 Announce Type: replace Abstract: Vision-based occupancy networks (VONs) provide an end-to-end solution for reconstructing 3D environments in autonomous driving. However, existing me

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Model Releases

Denoising-Aware Temporal Point Cloud Completion for 3D Crop Architecture Recovery and Phenotypic Trait Extraction

DGX agent

arXiv:2608.28343v1 Announce Type: new Abstract: High-throughput phenotyping depends on accurate 3D reconstruction of plants across growth stages, yet the development and evaluation of temporal complet

model-releasesarxiv-cs-cv

31 Aug 2026

Does Finetuning with Scientific Data Increase Hallucinations? A Multi-domain Factuality Evaluation of LLMs

arXiv:2606.21359v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to communicate and explain scientific concepts, yet their tendency to hallucinate poses significa

Entity-Memory Graph Retrieval Improves Evidence Coverage in Long-Conversation Question Answering

arXiv:2608.27925v1 Announce Type: new Abstract: Entity-Memory graph retrieval keeps dialogue turns as verbatim Memory nodes, links repeated mentions through shared Entities, and connects adjacent Memo

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

arXiv:2305.12474v4 Announce Type: replace Abstract: Large Language Models(LLMs) have demonstrated remarkable performance across various natural language processing tasks; however, how to comprehensive

EvoHarmBench: Breaking Content Moderation with Iterative Human-Like Evasion

arXiv:2608.27844v1 Announce Type: new Abstract: Existing evaluations of harmful content detection rely predominantly on static benchmarks, which struggle to reflect the interactive adversarial ecosyst

Ex-Sim(3)-Reg: 2D-3D Correspondence Pruning via Extended Sim(3) Registration

arXiv:2608.28096v1 Announce Type: new Abstract: Learning-based image-to-point-cloud (I2P) registration has garnered increasing attention in recent years. Nevertheless, existing methods still struggle

Explainable Diabetic Retinopathy Classification Using Vision Foundation Models

arXiv:2608.28207v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a major cause of preventable blindness, creating a need for accurate and trustworthy automated screening. This study invest

FedEHR-Agents: Federated Agentic Optimization for Automated EHR Modeling

arXiv:2608.27856v1 Announce Type: new Abstract: Recent advances in large language models are enabling autonomous clinical agents to perform increasingly complex electronic health record (EHR) modeling

Fidelity Is Not Enough: Dispatch-Level Instrumentation for Agentic Datasheet Extraction

arXiv:2608.28439v1 Announce Type: new Abstract: One model passed our fidelity check without ever opening the datasheet. We found it while qualifying models for an internal extraction service: a struct

FinExam-10K: When Retrieval Helps Financial Reasoning?

arXiv:2608.28155v1 Announce Type: new Abstract: Professional financial examinations require models to combine domain knowledge, calculation, and judgment, yet no benchmark covers the full CFA and FRM

First Make It Playable, Then Make It Good: Staged Interaction Learning for Small Dialogue-Game Agents

arXiv:2608.27672v1 Announce Type: new Abstract: We present Qwen-GuidePlay-2B, a 2B-parameter language model for dialogue-game interaction. We fine-tune Qwen3.5-2B using three steps: a) SFT on only suc

Fully Unleashing the Multimodal Attacker: Meta-Adaptive Jailbreaking of Vision-Language Models

arXiv:2608.27531v1 Announce Type: cross Abstract: The safety of large vision-language models is increasingly stress-tested by multimodal jailbreaks, yet existing attacks remain largely static at the m

FUSED: Forensic-Semantic Mixture-of-Experts for AI Inpainting Detection and Localization

arXiv:2608.28302v1 Announce Type: new Abstract: Diffusion-based inpainting models modify only a localized part of an image, while many AI-image detectors rely on global artifacts and do not localize.

GeBDA: Building Damage Assessment as Text-Based Sequence Prediction

arXiv:2608.28567v1 Announce Type: new Abstract: Conventionally, Building Damage Assessment (BDA) is tackled either with dedicated network architectures or by fine-tuning geospatial image foundation mo

Generalized Gibbs Ensemble Weighting for Forecast Combination

arXiv:2608.28116v1 Announce Type: new Abstract: Forecast combination is a reliable way to improve predictive performance when several forecasting models are available. Simple aggregation rules such as

GraspHOI: Full-Body 3D Human-Object Reconstruction with Finger-Level Grasps from a Single In-the-Wild Image

arXiv:2608.28386v1 Announce Type: new Abstract: Existing monocular full-body 3D human-object interaction (HOI) methods do not combine explicit finger-level grasp optimization with category-agnostic ob

How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models

arXiv:2608.28404v1 Announce Type: new Abstract: Video generation for autonomous driving cannot follow the web-scale route: driving data is expensive to collect, bound by privacy requirements, and cann

Improved off-policy training of diffusion samplers

arXiv:2402.05098v5 Announce Type: replace Abstract: We study the problem of training diffusion models to sample from a distribution with a given unnormalized density or energy function. We benchmark s

Knowing Before Answering: Decoding Language Models for Reliable RAG

arXiv:2608.27661v1 Announce Type: new Abstract: In Retrieval-Augmented Generation (RAG), retrieval may provide insufficient or conflicting information needed to answer a question. The system should no

Landau theory of quenched criticality in linear in-context learning

arXiv:2608.28059v1 Announce Type: cross Abstract: In-context learning (ICL) allows a pretrained model to infer a new task from examples supplied in its prompt without updating its parameters. In linea

Learning a Single Token to Replace Long System Prompts in LLMs

arXiv:2511.23271v2 Announce Type: replace Abstract: Long system prompts are widely used to steer Large Language Models (LLMs), but repeatedly processing them at inference time is inefficient and consu

Learning Fast Monomial Orders for Grobner Basis Computations

arXiv:2602.02972v2 Announce Type: replace-cross Abstract: The efficiency of Grobner basis computation, the standard engine for solving systems of polynomial equations, depends on the choice of monomia

Learning the Target Priors Before Image Translation: A Decoupled Training Paradigm for Cross-Modal Image Translation in Remote Sensing

arXiv:2608.28517v1 Announce Type: new Abstract: Cross-modal image translation in remote sensing must preserve source-observed content while matching the target-domain distribution. Existing methods jo

Learning to Difference: Adaptive Reversible Differencing (AdaRDiff) for Time Series Forecasting

arXiv:2608.28134v1 Announce Type: new Abstract: Reliable long-horizon time series forecasting is an important yet difficult problem. Trends and seasonality introduce complex temporal structure that ch

Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection

arXiv:2608.28375v1 Announce Type: cross Abstract: Global goodness-of-fit and discrepancy statistics can establish that a sample departs from a reference distribution without identifying which observat

Long Story Short: Story-level Video Understanding from 20K Short Films

arXiv:2406.10221v3 Announce Type: replace-cross Abstract: Recent developments in vision-language models have significantly advanced video understanding. Existing datasets and tasks, however, have nota

Manifold4D: Denoising on Point Cloud Rendered Manifolds for Video Re-shooting

arXiv:2608.28174v1 Announce Type: new Abstract: Video re-shooting re-renders a monocular video of a dynamic scene along a user-specified camera trajectory, and the dominant recipe supplies the target

Memorization Is Not Extraction: Tight Differential-Privacy Bounds and Audit Blind Spots

arXiv:2608.27782v1 Announce Type: cross Abstract: Memorization in large language models is measured through a zoo of definitions whose formal relations are unknown, and differential privacy (DP) is tr

Nested Byte-Level Vocabularies Are Cheap to Deploy and Expensive to Share: A Pre-Registered Negative Result

arXiv:2608.28151v1 Announce Type: new Abstract: A byte-level BPE tokenizer is an ordered list of merge rules, so applying only a prefix yields a vocabulary whose token identifiers are the first rows o

NL2AGBench: Benchmarking LLM Auto-Formalization for AlphaGeometry

arXiv:2608.28481v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated strong capabilities in natural language understanding and mathematical reasoning. Howe

Node-wise Feature Encoding for Neural Performance Prediction

arXiv:2608.27794v1 Announce Type: new Abstract: As neural networks are increasingly deployed on resource constrained edge devices, accurate prediction of latency and energy is critical for efficient n

Non-Uniform Quantisation for 3DGS Compression

arXiv:2608.28272v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, yet its high bitrate requirements pose significant challenges

NumBench: Diagnosing Counting Failures in Text-to-Image Models

arXiv:2608.28206v1 Announce Type: new Abstract: Text-to-image (T2I) models often generate the wrong number of objects, yet existing benchmarks are too small or weakly controlled to explain why. We int

OceanGym: A Benchmark Environment for Underwater Embodied Agents

arXiv:2509.26536v3 Announce Type: replace Abstract: We introduce OceanGym, the first comprehensive benchmark for ocean underwater embodied agents, designed to advance AI in one of the most demanding r

Off the Normal Path: Learning Spatial Density Models of Node Mobility

arXiv:2411.10997v2 Announce Type: replace-cross Abstract: We consider the problem of learning models of spatial density functions, representing the steady-state density of mobile nodes moving on a two

One Model for All: Universal Pre-training for EEG based Emotion Recognition across Heterogeneous Datasets and Paradigms

arXiv:2511.08444v2 Announce Type: replace Abstract: EEG-based emotion recognition is hampered by profound dataset heterogeneity (channel/subject variability), hindering generalizable models. Existing

PAMoR: Parameterized Affective Motion Generation in Real Time for Humanoid Robots

model-releasesarxiv-cs-ro

arXiv:2608.28213v1 Announce Type: new Abstract: People read a humanoid robot's motion in social settings not only for the action performed but for the affect conveyed. Motion carrying that affect has

PanelShield: Verifiable Closed-Loop Safe Planning for Robotic Industrial Panel Operation

model-releasesarxiv-cs-ro

arXiv:2608.28305v1 Announce Type: new Abstract: Industrial panel operation is knowledge-intensive and safety-critical. Beyond control recognition and action generation, execution must satisfy constrai

PCBnet: A Dataset and Automatic Construction of SPICE Netlists from Schematic Images

arXiv:2608.27923v1 Announce Type: new Abstract: Printed circuit boards (PCBs) are fundamental to modern electronic systems, yet AI-driven PCB design automation remains constrained by the lack of large

PersonaForge: Realistic Multi-Turn User Simulation for Agentic Systems

arXiv:2608.28378v1 Announce Type: new Abstract: Large language models are increasingly used as agentic workflow executors, yet existing training data and benchmarks largely assume informationally comp

Physics-informed learning for the inverse problem in resonant ultrasound spectroscopy

arXiv:2608.27590v1 Announce Type: cross Abstract: Inferring elastic constants from resonant ultrasound spectra is a nonlinear and typically overdetermined inverse problem based on finite spectral data

Post-Training VLMs for Video Mistake Detection

arXiv:2608.28406v1 Announce Type: new Abstract: Human mistakes are inevitable when following instructions, yet they can lead to severe consequences. As such, there has been an increased interest in de

Prequential posteriors

arXiv:2511.17721v2 Announce Type: replace-cross Abstract: Data assimilation is a fundamental task in updating forecasting models upon observing new data, with applications ranging from weather predict

Probabilistic Multi-Robot Gas Source Localization with Uncalibrated Sensors: A Distributed Estimation Approach

model-releasesarxiv-cs-ro

arXiv:2608.28214v1 Announce Type: new Abstract: Estimating environmental states with multi-robot systems becomes particularly challenging when robots are equipped with uncalibrated and therefore heter

QGPINNs: A Physics-Informed Neural Network Framework for Nonlocal Differential Equations on Quantum Graphs

arXiv:2608.28589v1 Announce Type: new Abstract: We propose QGPINNs, a physics-informed neural network framework developed in PyTorch for the numerical solution of nonlocal differential equations on qu

Quantifying Affective Bias in Low-Resource Media: Large-Scale Emotion Profiling of Bengali Headlines

arXiv:2510.17252v2 Announce Type: replace Abstract: News media can influence readers not only through the events they report but also through the emotional tone used to present them. This issue is esp

Quantization-Triggered Backdoors in Language Models: Cross-Quantizer Transferability and the Validation--Deployment Gap

arXiv:2608.27512v1 Announce Type: cross Abstract: Post-training quantization is often treated as a semantically neutral optimization for edge deployment of Large Language Models. When a full-precision